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11/10/2024 |
8:30 AM – 12:00 PM |
Golden Gate 1-2
W24: Social and Organizational Approaches to Optimize AI Design, Implementation, and Ongoing Use
Presentation Type: Workshop/Tutorial
Social and Organizational Approaches to Optimize AI Design, Implementation, and Ongoing Use
Presentation Time: 08:30 AM - 12:00 PM
Abstract Keywords: Governance of Artificial Intelligence, Diversity, Equity, Inclusion, Accessibility, and Health Equity, Fairness and Elimination of Bias, Evaluation, Informatics Implementation
Working Group: People and Organizational Issues Evaluation Working Group
Primary Track: Applications
Programmatic Theme: Clinical Informatics
With the widespread automation in healthcare it is increasingly feasible to deploy artificial intelligence (AI) methods and tools for clinical outcome prediction, image analysis, and other operational and clinical purposes. While AI tools aim to improve outcomes, their design and implementation can create new risks for patients, clinical personnel, and management. The use of AI lifecycles and implementation frameworks has been varied, and a particular shortcoming is a lack of guidance on broader issues with AI in healthcare such as health equity, safety, and ethical, legal, social and organizational implications. As the use of AI expands into practice more broadly, it is increasingly important to incorporate these considerations into each phase of the AI lifecycle. This collaborative workshop will explore these topics for AI system developers, decision-makers, healthcare professionals, and administrators from conceptualization through evaluation phases along the AI lifecyle. Capabilities that address social, organizational, equity, and safety risks form an essential pillar in the maturity of HCOs with respect to safe and effective use of AI.
The workshop is organized into three participant-engaging segments focusing on data and models, stakeholders and implementation, and evaluation and infrastructure. Workshop faculty will review key social and organizational issues, methods, and frameworks in each segment, and participants will work with the information in groups focused on specific real-world scenarios. At the end of the workshop, attendees will be able to highlight these considerations across the lifecycle for various stakeholders and use this to inform efforts at their own organizations.
Speaker(s):
Laurie Novak, PhD
Vanderbilt University Medical Center Dept of Biomedical Informatics
Craig Kuziemsky, PhD
MacEwan University
Elise Lambert, PhD
Texas State University
Saira Haque
Pfizer Pharmaceuticals
Carolyn Petersen, MS, MBI, FAMIA
Mayo Clinic
Joanna Abraham, PhD
Department of Anesthesiology and Institute for Informatics, Data Science and Biostatistics at Washington University in St. Louis, School of Medicine
Bonnie Kaplan, PhD
Yale University
Author(s):
Presentation Time: 08:30 AM - 12:00 PM
Abstract Keywords: Governance of Artificial Intelligence, Diversity, Equity, Inclusion, Accessibility, and Health Equity, Fairness and Elimination of Bias, Evaluation, Informatics Implementation
Working Group: People and Organizational Issues Evaluation Working Group
Primary Track: Applications
Programmatic Theme: Clinical Informatics
With the widespread automation in healthcare it is increasingly feasible to deploy artificial intelligence (AI) methods and tools for clinical outcome prediction, image analysis, and other operational and clinical purposes. While AI tools aim to improve outcomes, their design and implementation can create new risks for patients, clinical personnel, and management. The use of AI lifecycles and implementation frameworks has been varied, and a particular shortcoming is a lack of guidance on broader issues with AI in healthcare such as health equity, safety, and ethical, legal, social and organizational implications. As the use of AI expands into practice more broadly, it is increasingly important to incorporate these considerations into each phase of the AI lifecycle. This collaborative workshop will explore these topics for AI system developers, decision-makers, healthcare professionals, and administrators from conceptualization through evaluation phases along the AI lifecyle. Capabilities that address social, organizational, equity, and safety risks form an essential pillar in the maturity of HCOs with respect to safe and effective use of AI.
The workshop is organized into three participant-engaging segments focusing on data and models, stakeholders and implementation, and evaluation and infrastructure. Workshop faculty will review key social and organizational issues, methods, and frameworks in each segment, and participants will work with the information in groups focused on specific real-world scenarios. At the end of the workshop, attendees will be able to highlight these considerations across the lifecycle for various stakeholders and use this to inform efforts at their own organizations.
Speaker(s):
Laurie Novak, PhD
Vanderbilt University Medical Center Dept of Biomedical Informatics
Craig Kuziemsky, PhD
MacEwan University
Elise Lambert, PhD
Texas State University
Saira Haque
Pfizer Pharmaceuticals
Carolyn Petersen, MS, MBI, FAMIA
Mayo Clinic
Joanna Abraham, PhD
Department of Anesthesiology and Institute for Informatics, Data Science and Biostatistics at Washington University in St. Louis, School of Medicine
Bonnie Kaplan, PhD
Yale University
Author(s):
W24: Social and Organizational Approaches to Optimize AI Design, Implementation, and Ongoing Use
Description
